# cache: "pip"
          # cache-dependency-path: pyproject.toml
      - uses: actions/cache@v4
        id: cache
        with:
          path: ${{ env.pythonLocation }}
          key: ${{ runner.os }}-python-${{ env.pythonLocation }}-pydantic-v2-${{ hashFiles('pyproject.toml', 'requirements-tests.txt', 'requirements-docs-tests.txt') }}-test-v08
      - name: Install Dependencies

Then create a file `traefik.toml` with:

```TOML hl_lines="3"
[entryPoints]
  [entryPoints.http]
    address = ":9999"

[providers]
  [providers.file]
    filename = "routes.toml"
```

This tells Traefik to listen on port 9999 and to use another file `routes.toml`.

!!! tip

!!! tip "Astuce"
    Pour ceux qui se demandent, "AlexNet", "ResNet", et "LeNet" sont juste des noms de <abbr title="Techniquement, des architectures de modèles">modèles</abbr> de Machine Learning.

### Déclarer un paramètre de chemin

        with:
          python-version: "3.10"
          # Issue ref: https://github.com/actions/setup-python/issues/436
          # cache: "pip"
          # cache-dependency-path: pyproject.toml
      - name: Install build dependencies
        run: pip install build
      - name: Build distribution
        env:
          TIANGOLO_BUILD_PACKAGE: ${{ matrix.package }}
        run: python -m build

```{ .dockerfile .annotate }
# (1)
FROM python:3.9 as requirements-stage

# (2)
WORKDIR /tmp

# (3)
RUN pip install poetry

# (4)
COPY ./pyproject.toml ./poetry.lock* /tmp/

# (5)
RUN poetry export -f requirements.txt --output requirements.txt --without-hashes

# (6)
FROM python:3.9

# (7)
WORKDIR /code

# (8)

Sebastián Ramírez <******@****.***> 1714689451 -0700

Dann erstellen Sie eine Datei `traefik.toml` mit:

```TOML hl_lines="3"
[entryPoints]
  [entryPoints.http]
    address = ":9999"

[providers]
  [providers.file]
    filename = "routes.toml"
```

Dadurch wird Traefik angewiesen, Port 9999 abzuhören und eine andere Datei `routes.toml` zu verwenden.

!!! tip "Tipp"

* Crie um `templates` que você possa reutilizar posteriormente.
* Declare um parâmetro `Request` no *path operation* que retornará um template.
* Use o `template` que você criou para renderizar e retornar uma `TemplateResponse`, passe o nome do template, o request object, e um "context" dict com pares chave-valor a serem usados dentro do template do Jinja2.

```Python hl_lines="4  11  15-18"
{!../../../docs_src/templates/tutorial001.py!}
```

!!! note

```{ .dockerfile .annotate }
# (1)
FROM python:3.9 as requirements-stage

# (2)
WORKDIR /tmp

# (3)
RUN pip install poetry

# (4)
COPY ./pyproject.toml ./poetry.lock* /tmp/

# (5)
RUN poetry export -f requirements.txt --output requirements.txt --without-hashes

# (6)
FROM python:3.9

# (7)
WORKDIR /code

# (8)

* 🌐 Add Korean translation for `docs/tutorial/cors.md`. PR [#3764](https://github.com/tiangolo/fastapi/pull/3764) by [@NinaHwang](https://github.com/NinaHwang).

### Internal

* ⬆ Update coverage[toml] requirement from <7.0,>=6.5.0 to >=6.5.0,<8.0. PR [#5801](https://github.com/tiangolo/fastapi/pull/5801) by [@dependabot[bot]](https://github.com/apps/dependabot).